101. A simulated annealing heuristic for maximum correlation core/periphery partitioning of binary networks.
- Author
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Brusco, Michael, Stolze, Hannah J., Hoffman, Michaela, and Steinley, Douglas
- Subjects
STATISTICAL correlation ,GENETIC algorithms ,COMBINATORIAL optimization ,INFORMATION sharing ,INTELLIGENCE sharing - Abstract
A popular objective criterion for partitioning a set of actors into core and periphery subsets is the maximization of the correlation between an ideal and observed structure associated with intra-core and intra-periphery ties. The resulting optimization problem has commonly been tackled using heuristic procedures such as relocation algorithms, genetic algorithms, and simulated annealing. In this paper, we present a computationally efficient simulated annealing algorithm for maximum correlation core/periphery partitioning of binary networks. The algorithm is evaluated using simulated networks consisting of up to 2000 actors and spanning a variety of densities for the intra-core, intra-periphery, and inter-core-periphery components of the network. Core/periphery analyses of problem solving, trust, and information sharing networks for the frontline employees and managers of a consumer packaged goods manufacturer are provided to illustrate the use of the model. [ABSTRACT FROM AUTHOR]
- Published
- 2017
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